R in a Nutshell

Why learn R? Because it’s rapidly becoming the standard for developing statistical software. R in a Nutshell provides a quick and practical way to learn this increasingly popular open source language and environment. You’ll not only learn how to program in R, but also how to find the right user-contributed R packages for statistical modeling, visualization, and bioinformatics.

The author introduces you to the R environment, including the R graphical user interface and console, and takes you through the fundamentals of the object-oriented R language. Then, through a variety of practical examples from medicine, business, and sports, you’ll learn how you can use this remarkable tool to solve your own data analysis problems.

  • Understand the basics of the language, including the nature of R objects
  • Learn how to write R functions and build your own packages
  • Work with data through visualization, statistical analysis, and other methods
  • Explore the wealth of packages contributed by the R community
  • Become familiar with the lattice graphics package for high-level data visualization
  • Learn about bioinformatics packages provided by Bioconductor

“I am excited about this book. R in a Nutshell is a great introduction to R, as well as a comprehensive reference for using R in data analytics and visualization. Adler provides ‘real world’ examples, practical advice, and scripts, making it accessible to anyone working with data, not just professional statisticians.”

Table of Contents
Part I: R Basics
Chapter 1 Getting and Installing R
Chapter 2 The R User Interface
Chapter 3 A Short R Tutorial
Chapter 4 R Packages

Part II: The R Language
Chapter 5 An Overview of the R Language
Chapter 6 R Syntax
Chapter 7 R Objects
Chapter 8 Symbols and Environments
Chapter 9 Functions
Chapter 10 Object-Oriented Programming
Chapter 11 High-Performance R

Part III: Working with Data
Chapter 12 Saving, Loading, and Editing Data
Chapter 13 Preparing Data
Chapter 14 Graphics
Chapter 15 Lattice Graphics

Part IV: Statistics with R
Chapter 16 Analyzing Data
Chapter 17 Probability Distributions
Chapter 18 Statistical Tests
Chapter 19 Power Tests
Chapter 20 Regression Models
Chapter 21 Classification Models
Chapter 22 Machine Learning
Chapter 23 Time Series Analysis
Chapter 24 Bioconductor

Appendix. R Reference

Book Details

  • Paperback: 640 pages
  • Publisher: O’Reilly Media (December 2009)
  • Language: English
  • ISBN-10: 059680170X
  • ISBN-13: 978-0596801700
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